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PubMed2026

Benchmarking the OptiSpray-μPAC Workflow against a Traditional Nanospray Capillary Interface for Multiplexed Quantitative Proteomics.

Nanoflow liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) underpins modern quantitative proteomics, yet the column-to-mass spectrometer interface remains an important yet often underappreciated determinant of analytical depth, sensitivity, and reproducibility. Here, we benchmark an integrated workflow comprising the newly developed OptiSpray ion source and a micropillar array column (μPAC) cartridge against a conventional Nanospray Flex Source with an Accucore resin-packed capillary column. We performed a TMTpro 18-plex experiment across nine human cell lines on a FAIMS Pro-equipped Orbitrap Exploris 480. Following basic-pH reversed-phase fractionation, 12 fractions were analyzed on both workflow configurations under matched chromatographic gradient and acquisition conditions. Across both configurations, we quantified >9000 protein groups with highly comparable quantitative reproducibility and principal component clustering. Direct comparison of protein abundance ratios across cell lines showed agreement (Pearson R2 ≈ 0.7-0.8) without systematic bias. These results were achieved without workflow-specific optimization of the OptiSpray-μPAC platform, enabling direct transfer of established acquisition methods. Despite differences in column architecture, both configurations delivered comparable proteome coverage and quantitative fidelity. These findings establish the OptiSpray-μPAC workflow as a standardized alternative to conventional capillary-based interfaces, offering simplified operation while preserving quantitative performance.

Humans↗

PubMed2026

Dichalcogenide Fidaxomicin Derivatives to Probe Thiol-Mediated Uptake into Bacteria.

The natural product fidaxomicin (Fdx) is a narrow-spectrum antibiotic clinically prescribed for the treatment of Clostrodioides difficile infections. However, limited cellular uptake reduces its therapeutic potential, particularly against Gram-negative bacteria and mycobacteria. In this study, we investigated Thiol-Mediated Uptake (TMU) to promote the delivery of Fdx into bacterial cells. We synthesized a library of Fdx derivatives bearing cyclic dichalcogenide moieties and evaluated their antimicrobial properties against C. difficile and Mycobacterium tuberculosis, respectively. Remarkably, the synthetic Fdx derivatives retained strong levels of antibacterial activity, and the disulfide-containing analogs outperformed their all-carbon control counterparts in many instances. We then developed a systematic study to investigate the mechanistic impact of the introduced disulfide functionalities by conducting experiments with TMU inhibitors and quantifying intracellular accumulation in Mycobacterium bovis BCG, a model organism for M. tuberculosis, via LC-MS/MS. While complete disentanglement of the factors influencing activity was not feasible, features such as compound stability and lipophilicity were identified as significant contributors. Overall, the superior performance of disulfide analogs suggests that differences in cellular entry or intracellular processing, potentially related to TMU, are involved. This work highlights that TMU remains a viable approach for modulating the uptake of therapeutic agents into bacterial cells.

Sulfhydryl Compounds↗

PubMed2025

Site-Specific Profiling of RNA-Binding Proteins Enabled by Isotopic Signature-Enhanced Mass Spectrometry.

RNA-binding proteins (RBPs) ubiquitously regulate RNA throughout their lifespan, being extensively involved in cellular metabolism and genetic evolution. Therefore, comprehensive identification of the RNA-protein interactions, especially their interfaces with site-specific resolution, is significant to elucidate the intricate biological activities governed by RNA. Nevertheless, it remains challenging for data-dependent acquisition (DDA)-based proteomics to identify the RNA-cross-linked peptides in depth due to the low abundance and negative charge of modified peptides. To address such limitations, we developed an innovative method named "isoRIC" for profiling RNA-binding proteomes with site-specific resolution, which combines the metabolic labeling of isotopic nucleotides for photo-cross-linking of RNA-binding proteins and the real-time targeted LC-MS/MS analysis of RNA-cross-linked peptides. This method shows a dramatic improvement of sensitivity in identifying RNA-cross-linked peptides with low abundance as compared to the DDA-based proteomic approaches, enabling the discovery of novel RNA-binding proteins and precise mapping of RNA-protein binding interfaces at single amino acid resolution. We applied isoRIC in the context of pathogenic mutations and post-translational modifications to highlight the critical role of RNA-binding sites in modulating the RNA-binding ability.

RNA-Binding Proteins↗

PubMed2025

A clinically applicable method for early interstitial lung disease detection in incident rheumatoid arthritis cases: integration of protein biomarkers and clinical factors.

BACKGROUND: This study aimed to develop an early diagnostic method integrating proteomic biomarkers and clinical parameters for screening interstitial lung disease (ILD) in patients with newly diagnosed rheumatoid arthritis (RA) through a multi-phase research strategy. METHODS: A three-phase study was conducted: (1) Discovery: Tandem mass tag (TMT)-labeled quantitative proteomics with liquid chromatography-tandem mass spectrometry (LC-MS/MS) analyzed serum protein profiles in 5 RA-ILD and 5 RA-non-ILD patients, identifying candidates via bioinformatics. (2) Verification: Enzyme-linked immunosorbent assay (ELISA) validated candidates in an independent cohort (13 RA-ILD vs 14 RA-non-ILD). (3) Application: Biomarkers combined with clinical indicators (Krebs von den Lungen-6 [KL-6], age, sex) were evaluated in 110 patients (51 RA-ILD vs 59 RA-non-ILD) to build a predictive model. RESULTS: Proteomic analysis identified matrix metalloproteinase-3 (MMP3), von Willebrand factor (VWF), and other significantly differentially expressed proteins. ELISA validation confirmed that serum MMP3 and VWF levels were significantly higher in the RA-ILD group than in the RA-non-ILD group (p = 0.025 and 0.027, respectively). Expanded validation demonstrated superior diagnostic performance when combining MMP3 and VWF with KL-6 (area under the curve [AUC] = 0.90). The nomogram prediction model based on univariate analysis exhibited excellent discrimination (AUC = 0.89) and calibration. CONCLUSION: This systematic study from discovery to validation identified MMP3 and VWF as potential biomarkers for RA-ILD. The integrated predictive model combining these biomarkers with clinical parameters (KL-6, age, sex) provides a potential tool for early ILD screening in RA patients, offering novel strategies for early diagnosis and intervention of RA-ILD.

Humans↗

PubMed2026

Dynamic lysine acetylation and succinylation of platelet proteins regulates platelet storage lesion: mechanistic insights from multi-omics.

OBJECTIVES: Platelet storage lesion (PSL) severely impairs platelet function during storage, presenting a major hurdle in transfusion medicine; however, the dynamic interplay between global proteomic changes and post-translational modifications (PTMs) underlying these functional deteriorations remains insufficiently characterized. Here, we report the first comprehensive multi-omics analysis integrating global proteomics, acetylomics, and succinylomics to dissect the molecular dynamics during platelet storage. METHODS: We performed quantification of global proteomics, acetylome and succinylome based on TMT-labeled LC-MS/MS analysis, combined with antibody-affinity enrichment and purification. Dynamic molecular changes and functional transformation of platelet were also characterized under proper conditions stored for 1, 3, 5, 7 days, respectively. RESULTS: We systematically characterized 3,609 proteins, 1,308 acetylation sites, and 1,947 succinylation sites across multiple storage time points (D1, D3, D5, D7). We distinct temporal patterns of post-translational modifications, with succinylation showing more extensive coverage than acetylation in platelets. Pathway enrichment analysis revealed extensive metabolic reprogramming involving complement activation, energy metabolism, and cellular detoxification processes. The identification of specific motif patterns provided mechanistic insights into the functional specificity of these modifications. Random forest machine learning identified 20 core regulatory proteins representing critical nodes in PSL development. Furthermore, we employed real - time quantitative polymerase chain reaction (RT - QPCR) to measure the expression levels of key genes related to platelet function and PTM - associated pathways. CONCLUSION: By mapping the interplay between proteomic abundance shifts and PTM dynamics, this study provides a multidimensional understanding of PSL, establishing a foundational framework for optimizing storage protocols and enhancing transfusion safety.

Blood Platelets↗

PubMed2026

An Integrated Proteomics and Genomics Approach to Identify Essential Protein Kinases During Human Trophoblast Development.

In the developing human placenta, three subtypes of trophoblast cells, cytotrophoblasts (CTBs), extravillous trophoblasts (EVTs), and syncytiotrophoblasts (STBs), mediate critical functions essential for a successful pregnancy. CTBs constitute the stem/progenitor compartment and differentiate into STBs and EVTs within the floating and anchoring villi, respectively. STBs establish the maternal-fetal exchange interface and secrete human chorionic gonadotropin (hCG), a hormone vital for the maintenance of early pregnancy. EVTs anchor the maternal endometrium and invade the uterine tissue to remodel maternal cells, supporting implantation and progression of pregnancy. In this study, we used human trophoblast stem cells (hTSCs) as a model system and performed quantitative, label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) to profile the proteome and phosphoproteome in TSC stem state (analogous to undifferentiated CTBs) and following their differentiation to STBs and EVTs. Through a multiomics approach, we integrated our proteomics data with global gene expression profiles to correlate cell-type specific gene and protein expression during human trophoblast development. We also identified global phosphoproteome and analyzed kinases that are specifically active in hTSC stem state, as well as in differentiated STBs and EVTs. We experimentally validated specific kinases, such as BUB1B, PAK6, PKYMT1, and TNIK, that are essential for maintaining the hTSC stem-state. Additionally, atypical protein kinase C isoforms PKCζ are essential for STB development, whereas PTK2B, SRC, TRIO, and LYN are important for EVT development. Our findings highlight key kinases uniquely required for specific stages of trophoblast development during human placentation and suggest that pharmacological inhibition of these kinases could negatively impact the placentation process during pregnancy.

Humans↗

PubMed2026

Transcriptomic and proteomic signatures underlying nymphal adaptation and foam production in the forage pest Mahanarva spectabilis.

The spittlebug Mahanarva spectabilis (Distant, 1909) (Hemiptera: Cercopidae) is an important pest of forage grasses in South America, where its nymphs cause pasture damage by feeding on xylem sap and producing a characteristic foam that protects them against environmental stressors. To investigate the molecular basis of this adaptation, we integrated RNA-seq analysis of nymphs with LC-MS/MS proteomics of the Batelli gland, the primary source of foam secretion. De novo assembly of 100,666 unigenes revealed broad functional diversity, with strong representation of detoxification enzymes (CYP450s, GSTs, UGTs, carboxylesterases), transporters and ion pumps, cuticle proteins, and stress- and immunity-related genes. Nearly 16% of loci exhibited alternative splicing, particularly within detoxification, chemosensory and osmoregulatory gene families, highlighting evidence of transcriptomic variability. Signal peptide and secreted protein predictions identified 168 high-confidence candidate secreted proteins, including detoxification enzymes, proteases, structural proteins and immune-related factors, several of which are consistent with antimicrobial and surfactant-related functions. Proteomic profiling of the Batelli gland confirmed 500 proteins, enriched in chaperones, metabolic enzymes, detoxification pathways and osmoregulatory components, with the most abundant proteins corresponding to Hsp70 chaperones, ATP synthases, cuticle proteins and carbonic anhydrases. Together, these results provide an integrative transcriptomic and proteomic overview for M. spectabilis nymphs, highlighting genes and proteins associated with xylem feeding, foam production and responses potentially related to environmental stress tolerance. This comprehensive dataset not only advances the understanding of spittlebug biology but also identifies candidate molecular targets that may inform innovative strategies for controlling nymphal stages and mitigating spittlebug damage in forage systems.

Animals↗

PubMed2026

Comparison of Proteomic Analysis of Cerebrospinal Fluid From Neurological Patients With and Without Amyotrophic Lateral Sclerosis.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder characterised by progressive muscle weakness in both bulbar and extremity muscles, leading to a diverse clinical phenotype with motor and non-motor symptoms. Approximately 85% of ALS cases are sporadic (sALS), while the remaining 10%-15% are familial (fALS). Biological biomarkers of sporadic ALS remain poorly understood, hindering precise patient screening, delaying diagnosis and negatively affecting prognosis. This study aims to identify potential proteomic biomarkers by comparing the cerebrospinal fluid (CSF) of sALS patients with that of patients suffering from other neurological diseases. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used for proteomic profiling of CSF samples from 24 sALS patients and 26 patients with other neurological diseases. The complete protein expression profiles were compared using a two-tailed Student's t-test, with a p < 0.05 considered statistically significant with additional FDR correction at the 0.1 level. Proteomic analysis of CSF samples identified significant quantitative changes in 96 proteins with threshold p < 0.05 and 74 proteins with FDR < 0.1 between sALS and non-ALS patients, including alterations in proteins associated with neurodegenerative processes, such as amyloid precursor proteins and inflammatory markers. CSF proteomic analysis reveals altered inflammatory and neurodegenerative metabolic pathways, providing valuable insights into the proteomic landscape of sALS. Several dysregulated proteins were consistent with the disease mechanisms highlighted in previous studies. These findings represent a step forward in developing personalised approaches for diagnosing and managing the disease.

Humans↗

PubMed2026

Comparative Genome-Wide Association Studies of Metabolites and Grain-Related Traits in Common Wheat.

The metabolome is highly diverse and the closest layer to phenotype; therefore, it is commonly regarded as a bridge between the genome and phenome in plants. Here, we performed large-scale metabolome analysis using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and 33 grain-related traits in a diverse panel of natural accessions and a recombinant inbred line (RIL) population. We identified a new network of 2286 associations between 947 metabolites and 33 grain-related traits. Systematic integration of metabolic genome-wide association study (mGWAS) and metabolic quantitative trait locus (mQTL) analyses identified 33 566 significant single-nucleotide polymorphisms (SNPs) and 3128 mQTL. Thirteen annotated metabolites co-localized within a physical interval on 7A. Integration of metabolite-based and phenotype-based GWAS and QTL revealed an overlapped region for gibberellin A4 (GA4) content and grain roundness on 4A. Phenotyping of an ethyl methanesulfonate (EMS)-induced mutant confirmed the role of TaSDR in regulating GA4 content and grain morphology. These findings provide novel insights into the metabolic pathways influencing key grain-related traits and advance our understanding of the complex molecular mechanisms regulating grain metabolites and phenotypes in wheat. The identified metabolic markers and candidate genes provide valuable targets for molecular breeding programs aimed at improving wheat yield and quality.

QTL↗

PubMed2026

Machine Learning and Metabolomics to Characterize Warburg-Like Metabolic Subtypes in Human Retinal Endothelial Cells Exposed to Risk Factors Associated With Proliferative Diabetic Retinopathy.

PURPOSE: High glucose (HG), hypoxia (Hyp), and their combination are major risk factors for proliferative diabetic retinopathy (PDR). Although these conditions induce features of the Warburg-like metabolic reprogramming in human retinal endothelial cells (HRECs), it remains unclear whether they produce distinct metabolic and angiogenic subtypes. This study aimed to characterize the Warburg-like-associated metabolic heterogeneity induced by these PDR-related risk factors and evaluate the ability of supervised machine-learning models to distinguish these subtypes. METHODS: HRECs were cultured under normoglycemic, HG, Hyp (2% O2), and combined HG-Hyp conditions. Untargeted LC-MS/MS metabolomics quantified metabolites spanning carbohydrates, amino acids, nucleotides, and lipids. Principal component analysis (PCA) assessed overall metabolic variation, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis identified metabolic pathways associated with angiogenesis. In vitro angiogenesis assays measured endothelial tube formation and branching. Nine supervised classifiers (decision tree, logistic regression, naïve Bayes, random forest, K-Nearest Neighbors, neural network, gradient boosting, AdaBoost, and Support Vector Machine) were trained on the highest-ranked metabolites selected by the Information Gain Ratio feature-ranking approach. Model performance was evaluated using 10-fold cross-validation, leave-one-out cross-validation (LOOCV), permutation testing, and a classifier stability analysis under biologically meaningful distributional shift using an independent chemically induced hypoxia model (CoCl2). RESULTS: PCA revealed partial separation of metabolic profiles across conditions, indicating different Warburg-like metabolic subtypes. The combined HG-Hyp condition exhibited enhanced angiogenic potential relative to either HG or Hyp alone. KEGG pathway enrichment analysis identified fatty acid biosynthesis and elongation among the most significantly enriched pathways in HRECs under combined HG-Hyp conditions, alongside amino sugar and nucleotide sugar metabolism, glycerophospholipid metabolism, the pentose phosphate pathway, and glycolysis/gluconeogenesis. Supervised machine-learning classifiers distinguished these metabolic subtypes, with AdaBoost and gradient Boosting showing the most balanced, reproducible performance across 10-fold cross-validation, LOOCV, and permutation testing, and remaining the most reliable classifiers under domain-shift testing (area under the curve = 0.88, P = 0.0061). CONCLUSIONS: In this exploratory analysis, HG, Hyp, and their combination drive metabolically and functionally distinct subtypes of Warburg-like metabolic reprogramming in HRECs, with HG-Hyp in combination producing a highly angiogenic phenotype. Boosting-based ensemble classifiers provide a promising framework for detecting these subtypes even under domain-shift conditions, warranting validation in larger independent datasets. TRANSLATIONAL RELEVANCE: Integrating metabolomics with machine-learning classification offers a strategy to identify Warburg-like metabolic subtypes in retinal endothelial cells, providing insights into angiogenic mechanisms and guiding the development of targeted diagnostics or therapeutics for PDR.

Humans↗

PubMed2025

Mutations in the transcriptional regulator MAB_2885 confer tedizolid and linezolid resistance through the MmpS-MmpL efflux pump MAB_2302-MAB_2303 in Mycobacterium abscessus.

Mycobacterium abscessus (MAB) is a clinically significant multidrug-resistant (MDR) pathogen, particularly implicated in pulmonary infections among cystic fibrosis (CF) patients. Tedizolid (TZD), an oxazolidinone-class antibacterial drug, has been recommended as an alternative treatment for MAB-infected patients who are intolerant to or whose isolate is resistant to first-line drugs including linezolid (LZD). To investigate the TZD resistance mechanisms in MAB, we isolated 23 TZD-resistant MAB mutants and performed whole-genome sequencing (WGS) to identify resistance-associated genes. Frequent mutations were identified in MAB_2885, encoding a putative TetR transcriptional regulator, and MAB_2303, encoding a putative mycobacterial membrane protein large (MmpL). Drug susceptibility testing confirmed that MAB_2885 mutations contribute to both TZD and LZD resistance in MAB. RNA-seq analysis revealed that restoring wild-type MAB_2885 in mutants downregulated the MAB_2302-MAB_2303. Electrophoretic mobility shift assay (EMSA) showed the MAB_2885 protein binds to its target sequence upstream of MAB_2302-MAB_2303, further confirming their regulatory relationship. The W91R mutation in the MAB_2885 protein was found to impair its DNA-binding activity compared to the wild-type. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis confirmed that MAB_2302-MAB_2303 functions as a TZD efflux pump. Additionally, overexpression of MAB_2885 in M. abscessus subsp. bolletii and M. abscessus subsp. massiliense also increased their TZD susceptibility and downregulated their respective MmpS-MmpL orthologs. Overall, our study demonstrates that mutations in MAB_ 2885 contribute to TZD and LZD resistance by disrupting the negative regulation of the downstream MAB_2302-MAB_2303, which functions as a direct efflux pump for TZD. These findings provide new insights into oxazolidinone resistance mechanisms in MAB and identify potential biomarkers for detecting drug resistance.

Mycobacterium abscessus↗

PubMed2026

Non-invasive embryo assessment: Cell-free DNA-based genetic testing and amino acid metabolomics in relation to morphology: A case-control study.

BACKGROUND: Cell-free DNA (cfDNA) in spent culture medium (SCM) offers a non-invasive option for preimplantation genetic testing, but its low concentration and fragmentation reduce clinical reliability. Combining genetic assessment with metabolomic profiling may provide complementary information about embryo competence. OBJECTIVE: This study assessed pre-analytical cfDNA processing workflows and examined whether SCM amino acid metabolic patterns could act as practical markers of embryo quality. MATERIALS AND METHODS: In this case-control study (2021-2023), 90 embryos were evaluated using fluorescence in situ hybridization or array comparative genomic hybridization. SCM samples underwent rapid boiling, silica-based purification, or whole-genome amplification (WGA). Sex determination was performed using quantitative polymerase chain reaction (qPCR). For cfDNA quality control and aneuploidy screening, the multiplex IRFiling kit and quantitative fluorescent polymerase chain reaction (QF-PCR) were used. Amino acid profiles across embryonic developmental stages and quality grades were quantified via liquid chromatography-tandem mass spectrometry. RESULTS: Rapid boiling resulted in complete failure of DNA amplification. Conversely, silica-based purification yielded 70.0% concordance for qPCR-based sexing and 56.7% for QF-PCR. WGA achieved the highest efficacy (73.3% qPCR and 56.7% QF-PCR concordance), although quality control checks flagged occasional misclassifications. LC-MS/MS profiling revealed significantly elevated alanine and arginine levels in tripronuclear embryos. Furthermore, high-quality blastocysts exhibited elevated glutamic acid levels alongside a pronounced overall depletion of extracellular amino acids compared to low-quality counterparts and controls. CONCLUSION: WGA improves cfDNA detectability and qPCR accuracy compared with boiling or purification, but remains inadequate as a standalone screening approach. SCM amino acid profiling provides informative, complementary metabolic signatures of developmental competence, supporting a multimodal strategy for non-invasive embryo assessment.

Amino acid metabolism↗

PubMed2025

Multi-Omics and Integrative Analytics in Natural Products Discovery.

Natural products (NPs) have long been an essential source of new bioactive compounds for drug discovery; however, traditional methods for screening and isolating these compounds can be slow and often yield diminishing returns. Fortunately, advanced multi-omics and computational approaches present powerful solutions to these challenges. This review highlights innovative methodologies that integrate metabolomics, genomics, transcriptomics, and proteomics with bioinformatics and analytical chemistry to accelerate NP discovery. For instance, untargeted metabolomics platforms like high-resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS) and Global Natural Products Social (GNPS) molecular networking allow for comprehensive profiling of new compounds, while targeted isotope-labeling strategies enhance this process. Additionally, genome and metagenome mining tools such as antibiotics and secondary metabolite analysis shell (antiSMASH), Deep Biosynthetic Gene Cluster (DeepBGC), and Pipeline for Reconstructing Integrated Syntheses of Metabolites (PRISM) quickly identify biosynthetic gene clusters (BGCs) in both cultured and uncultured organisms, often using heterologous expression to validate products. Transcriptomic analyses, including RNA sequencing (RNA-seq), co-expression networks, and fluxomics, help clarify how pathways are regulated, while quantitative proteomics techniques like tandem mass tags/isobaric tags for relative and absolute quantitation (TMT/iTRAQ) and label-free methods, along with chemoproteomics approaches such as cellular thermal shift assay and thermal proteome profiling (TPP), uncover molecular targets and their mechanisms of action. This review also places significant emphasis on the role of artificial intelligence (AI) and machine learning (ML) in integrating multi-omics data, spanning activities from constructing gene-metabolite correlation networks to leveraging knowledge graphs and graph neural networks for data fusion and functional prediction. Finally, this review concludes by discussing the synergistic benefits of multi-omics for natural-product discovery, addressing current technical challenges, and exploring future directions toward high-throughput, intelligent data integration for next-generation NP research.

Biological Products↗

PubMed2026

Proteomic insights into azoospermia: protein differences in testicular tissue between non-obstructive and obstructive azoospermia patients.

Non-obstructive azoospermia (NOA) and obstructive azoospermia (OA) are the main classifications of severe male infertility, but the molecular mechanism of NOA remains poorly understood. This study aimed to identify potential biomarkers and pathological mechanisms by comparing the proteomic differences in testicular tissues of NOA and OA patients. Through proteomic analysis based on liquid chromatography-tandem mass spectrometry (LC-MS/MS) of testicular samples from 5 NOA patients and 5 OA patients, we identified 5264 proteins, among which 717 differentially expressed proteins (DEPs) were found between the two groups (242 upregulated and 475 downregulated in NOA). Bioinformatics analysis indicated that these DEPs were significantly associated with reproductive development, gametogenesis, and cell structural stability. On the basis of this, six candidate proteins, including dysferlin (DYSF), myoferlin (MYOF), mitsugumin 53 (MG53), cluster of differentiation 63 (CD63), caveolin-3 (CAV3), and calpain-3 (CAPN3), were selected from the DEPs and verified in an expanded sample set (37 NOA cases and 28 OA cases) through quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot, confirming their dysregulation in NOA. These findings provide new proteomic insights into NOA, highlighting the disruption of membrane repair and structural pathways, and offer potential biomarkers for understanding its pathogenesis.

Humans↗

PubMed2026

Improved comprehensive profiling of fecal bile acids through chemical derivatization combined with HPLC-MS/MS analysis.

Bile acids (BAs) facilitate the digestion and absorption of fats and influence lipid and glucose homeostasis, making them potential therapeutic targets for obesity and related metabolic disorders. The liver and intestinal microbiota modify BAs structurally, generating diverse chemical forms and isomers. Comprehensive profiling of the BA pool is critical for understanding their key biological functions and as a therapeutic approach for related diseases. High-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) is usually chosen as the preferred method for BA detection due to the complex chemical structures, the wide range of actual concentrations and the complexity of fecal sample matrices. However, free BAs are difficult to ionize, resulting in low detection signals and a lack of characteristic structural fragments to assist in structural identification. In this method, the labeling reagent (2-aminoethyl) trimethylammonium (AETMA) is employed to label the carboxyl group of BAs. Compared with underivatized BAs, the detection sensitivity of unconjugated BAs was enhanced by 25-180 fold, while that of conjugated BAs increased by 6-160 fold. It also generates unique fragment ions and enhances MS response, facilitating the discovery of potential BAs. Methodological parameters were validated using 38 BAs as representatives. Through methodological validation, it was verified that the precision, recovery, matrix effect and stability parameters of the method met acceptable criteria. We also identified 61 confirmed BAs and 55 additional candidate BAs in human pooled fecal samples. It has been successfully applied to fecal BA analysis in obese populations, providing valuable insights into potential therapeutic strategies for obesity.

Tandem Mass Spectrometry↗

PubMed2026

On-filter fractionation by empFASP improves identification of membrane peptides in proteomic experiments.

Membrane proteins remain among the most analytically challenging targets in bottom-up proteomics due to their limited solubility and low abundance of protease-accessible sites within transmembrane domains. In addition, hydrophobic peptides are frequently lost during detergent removal and the on-filter processing steps. Here, we present empFASP, a straightforward on-filter-fractionation-based modification of the enhanced filter-aided sample preparation (eFASP) workflow that enhances recovery of membrane-embedded peptides otherwise lost during digestion and cleanup. The method combines controlled on-filter inversion with sequential ethyl acetate extraction at defined pH values, enabling recovery of peptide material retained on the filter and redistributed into detergent micelles. Compared with SP3 and SP4 in HEK293T lysates, empFASP increased unique hydrophobic peptide identifications by up to 48% and increased the proportion of detected transmembrane peptides. Application to mouse mitochondrial membranes and phosphatidylethanolamine-deficient and PE-containing Escherichia coli membranes showed that the additional fractions of empFASP contribute complementary recovery of hydrophobic and membrane-associated peptides, with the strongest gains observed at the peptide level. Because empFASP requires no specialized reagents or instrumentation, it can be readily implemented in standard proteomics workflows to improve coverage of membrane-embedded regions. SIGNIFICANCE: The empFASP (enhanced membrane peptide) workflow offers a practical solution to one of the persistent limitations in membrane proteomics-the underrepresentation of hydrophobic and transmembrane peptides in standard digests. By integrating simple pH-controlled extractions into an on-filter format, empFASP recovers peptides otherwise lost through adsorption or detergent micelle retention, substantially improving coverage of the membrane proteome. This method expands the analytical reach of bottom-up proteomics without requiring specialized instrumentation, making it immediately applicable for studies of membrane topology, protein-lipid interactions, and the structural consequences of altered membrane composition.

Proteomics↗

PubMed2026

Quantitative N-glycoproteomic analysis reveals glycosylation signatures of plasma immunoglobulin G in sepsis.

INTRODUCTION: Sepsis is a life-threatening condition resulting from organ dysfunction due to a dysregulated immune response to infection. Immunoglobulin G (IgG) plays a role in modulating immune responses. However, the precise IgG subclass-specific N-glycosylation profiles in patients with sepsis remain poorly characterized. METHODS: This study aimed to define the site-specific N-glycosylation signatures of plasma IgG subclasses in sepsis patients with different prognoses using quantitative glycoproteomics. By employing our established GlycoQuant strategy, we quantified the intact N-glycopeptides (IGPs) of IgG subclasses in 40 healthy controls and 40 sepsis patients with a clear prognosis. RESULTS: We identified 12 IGPs with altered abundances between patients with sepsis and healthy controls. After Benjamini-Hochberg (BH) correction of the 31 outcome-stratified IGP comparisons, IGP24 and IGP25 remained significant and met the prespecified fold-change criterion. Global BH correction across 124 IGP-clinical parameter correlations retained positive associations of IGP19, IGP22, and IGP23 with procalcitonin (PCT). In exploratory outcome-stratified ROC analyses, candidates were selected using the original unadjusted P-value and fold-change screen; five IGPs were evaluated, with IGP25 and IGP24 yielding the highest individual AUCs. Collectively, our findings underscore the potential of IgG subclass-specific glycosylation profiling as a novel translational approach for clinical applications in sepsis management. SIGNIFICANCE: Sepsis remains a leading cause of global mortality, with patient outcomes heavily dependent on timely diagnosis and accurate prognosis. The dysregulated host immune response, particularly involving immunoglobulins, is central to its pathophysiology. This study provides a significant advance in the field of clinical glycoproteomics by applying a quantitative, site-specific strategy to delineate the plasma IgG subclass N-glycosylation landscape in sepsis. We report, for the first time, a panel of subclass-specific intact IgG N-glycopeptides (IGPs) that are significantly altered in sepsis patients compared to healthy controls. The identified IGPs not only demonstrate diagnostic and prognostic potential but also show a significant correlation with procalcitonin, a key clinical severity index. These findings bridge a critical knowledge gap by moving beyond bulk IgG glycosylation analysis to subclass-resolved profiling, offering novel molecular insights into sepsis immunopathology. The identified glycosylation signatures hold substantial translational promise as a foundation for developing innovative, glycan-based biomarker panels to improve the precision management of this heterogeneous and life-threatening syndrome.

Humans↗

PubMed2026

Subcellular Proteomic Analyses Reveal REEP5 Knockdown in the Mouse Heart Disrupts Mitochondrial Networks.

Receptor Expression-Enhancing Protein 5 (REEP5) is a cardiac-enriched, membrane-shaping protein localized to the sarco(endo)plasmic reticulum (SR/ER), where it supports membrane network architecture and cardiomyocyte function. While REEP5 has been implicated in calcium handling and contractility, its role in regulating inter-organelle communication and mitochondrial homeostasis remains less well-understood. In this study, we used recombinant adeno-associated virus serotype 9-mediated shRNA knockdown of Reep5 in mouse hearts, combined with subcellular fractionation and data-independent acquisition mass spectrometry, to define proteomic remodeling across microsomal (SR/ER), mitochondrial, and cytosolic compartments. Loss of REEP5 altered the composition of SR/ER membrane-shaping proteins, including upregulation of RTN4, ATL3, and CKAP4, suggesting a partial compensatory response. Microsomal, mitochondrial and cytosolic proteomes exhibited broad reorganization, with enrichment of proteins involved in redox adaptation and proteostasis, alongside depletion of mitochondrial import machinery and antioxidant enzymes. Imaging of isolated cardiomyocytes confirmed fragmented mitochondrial networks and increased reactive oxygen species, consistent with proteomic signatures of disrupted mitochondrial dynamics and oxidative stress. Gene ontology enrichment across all fractions highlighted widespread dysregulation in organelle-specific processes, including translation, protein localization, and metabolic remodeling. Notably, several altered pathways converged on mitochondria-associated membranes, suggesting that REEP5 may support SR/ER-mitochondria tethering and functional crosstalk. These findings position REEP5 as a key regulator of organelle homeostasis in the heart and underscore how its loss disrupts mitochondrial integrity and inter-organelle communication across cellular compartments.

Animals↗